Early, rapid and accurate diagnosis facilitates the timely and appropriate treatment of diseases, conditions and disorders, and enables selection of the most appropriate therapeutic interventions. The diagnosis and staging of diseases often involves many different diagnostic procedures, which in some cases have the disadvantages of being invasive, and/or prone to errors both due to limited sensitivity, and/or specificity, sampling variability, and technician variability. In the case of invasive testing may result in morbidity and occasionally even mortality. Genetic based diagnosis has been developed for a variety of diseases, to assess the presence, or the predisposition to, likelihood of remission and achievement of remission, response to therapeutic intervention or reoccurrence of such a disease. Such tests may also enable prognostic stratification, so as to determine those patients that need more aggressive therapeutic interventions and more intensive monitoring. Although there are several genetic assays available to identify the presence of gene mutations and chromosomal abnormalities, including polymerase chain reaction analysis, FISH and cytogenetic analysis, the identification of specific genetic changes is not always a direct indicator of a disease or a disorder and the likely aggressiveness of the underlying pathological process or indeed its likely responsiveness to therapy and it cannot thus be relied upon as an accurate prognostic indicator. However, changes in the overall patterns and/or expression levels of various genes and their corresponding proteins in a tissue or body fluid sample relative to a pre-disease-state, other stages of the disease or relative to negative and/or normal controls, can also be used to diagnose, stage and monitor disease and disorders. Such patterns of gene expression or protein expression may also be useful for prognostic stratification.
Therefore, there is a pressing need in the art to identify a differential gene expression pattern of a plurality of genes in a bodily sample that is reliably indicative of a particular disease, disorder and condition, or stage thereof, or predilection for. There is also a pressing need for such a display or fingerprint to be easily obtained from the patient, test or control individual. Such a fingerprint or ‘picture’ would be of use in diagnosing, predicting and/or detecting the presence or absence of a disease, disorder or condition, in assessing the response to a particular therapeutic intervention, in predicting the likelihood of a response to a particular therapeutic intervention or procedure, for predicting the extent and aggressiveness of any necessary therapeutic intervention, for the selection of a specific treatment from a selection of potential of therapeutic interventions, for prognostic stratification to determine the likely progression of the disease or disorder, or of disease-free survival with and without treatment for any individual with a particular disease or a condition, and in monitoring the progression of a disease process, and/or the impact of treatment on disease states or conditions.
Such gene expression patterns though are cumbersome to produce as they involve the preparation of RNA from a tissue sample and furthermore gene expression arrays are subject to technical problems including the fact that such arrays are not optimised for individual genes and that representation of the mRNA species population can be adversely influenced by the amplification procedures that are sometimes necessary if only a small amount of mRNA is present. There is consequently a need for a method that enables diagnostic patterns to be derived from body fluids. The measurement of soluble proteins released from cells by processes such as secretion of protein isoforms that are usually cell membrane associated and the derivation of patterns of such proteins therein, provides a simple method for diagnosing, predicting and/or detecting the presence or absence of a disease, disorder or condition, in assessing the response to a particular therapeutic intervention, in predicting the likelihood of a response to a particular therapeutic intervention or procedure, for predicting the extent and aggressiveness of any necessary therapeutic intervention, for the selection of a specific treatment from a selection of potential of therapeutic interventions, for prognostic stratification to determine the likely progression of the disease or disorder, or of disease-free survival with and without treatment for any individual with a particular disease or a condition, and in monitoring the progression of a disease process, and/or the impact of treatment on disease states or conditions.
In some instances where the power of an individual test is limited, gene expression signatures or patterns may be combined with protein expression signatures or patterns to derive nested genomic/proteomic patterns that may be used in diagnosing, predicting and/or detecting the presence or absence of a disease, disorder or condition, in assessing the response to a particular therapeutic intervention, in predicting the likelihood of a response to a particular therapeutic intervention or procedure, for predicting the extent and aggressiveness of any necessary therapeutic intervention, for the selection of a specific treatment from a selection of potential of therapeutic interventions, for prognostic stratification to determine the likely progression of the disease or disorder, or of disease-free survival with and without treatment for any individual with a particular disease or a condition, and in monitoring the progression of a disease process, and/or the impact of treatment on disease states or conditions.
CD Antigens:
Lymphocytes and other leukocytes express large numbers of different cell surface antigens that are associated with the cell surface membrane. This cell membrane anchoring is often achieved through the presence of a hydrophobic transmembrane domain that spans the cell membrane although other mechanisms for cell surface linkage also exist. The differential expression of such cell surface associated molecules can be used to identify distinct leukocyte cellular subsets that perform different functions. These cell surface molecules or ‘antigens’ are known to serve a broad range of critically important cellular functions (many of which are related to immune function) and include: receptors for growth factors, molecules that mediate cell-to-cell interactions, receptors for viral adhesion, (such as CD4, CD112 and CD5 155), immunoglobulins, cell adhesion molecules, mediators of complement stimulation, enzymes and ion channels. These cell surface antigens can be identified with monoclonal antibodies or other ligands, each of which recognises with a varying degree of specificity a different cell surface antigen (or sub-determinant on any individual cell surface antigen). An international workshop was established to derive a systematic nomenclature for the monoclonal antibodies that recognised antigens present on the cell surface of human leukocytes (The cluster of differentiation (CD) antigens defined by the First International Workshop on Human Leukocyte Differentiation Antigens. Hum Immunol. 1984 September; 11(1): 1-10). As a result of the statistical ‘cluster analysis’ method used to rationalize and map these monoclonal antibodies to specific antigens, these molecules came to be known as cluster of differentiation (CD) antigens, or CD molecules/antigens (Kishimoto et 20 al., 1996 Proceedings of the Sixth International Workshop and Conference held in Kobe, Japan. 10-14 Garland Publishing Inc. New York, USA).
The discovery of CD antigens and the monoclonal antibody technology used to define them was a direct result of the work of one of the inventors of the present application (Dr. César Milstein) who invented monoclonal antibody technology with his colleague Georges Kohler (Kohler and Milstein). In their classic paper (Continuous cultures of fused cells secreting antibody of defined specificity Nature 1975, Aug. 7, 256 (5517), 495-7) Kohler and Milstein described how monoclonal antibodies of a single defined specificity could be produced by the fusion of myeloma cells with plasma cells. Kohler and Milstein were awarded the Nobel Prize for Medicine and Physiology for this work. In collaboration with Andrew McMichael in Oxford, Milstein subsequently raised and identified monoclonal antibodies to the first non-human (CD4) and human (CD1) CD antigens (McMichael et al. A human thymocyte antigen defined by a hybrid myeloma monoclonal antibody, Eur. J. Immunol. 1979 March; 9(3):205-10).
The criteria necessary to assign a CD status to any given cell surface leukocyte molecule has changed as a result of technological advances achieved since the 1970s. At that time, clustering depended exclusively on the statistical revelation of similarities in the staining pattern of two or more antibodies that had been analysed on multiple different tissues and cell lines. However, presently a CD molecule is additionally also typically classified on the basis of its molecular characteristics, and structure (Bernard and Boumsell). A current list of CD antigen markers as of the last international workshop has been compiled (Table 43). This list was downloaded from the URL: hcdm.org/CD1 toCD350.htm on Nov. 6, 2007, and is updated at regular intervals. The number of CD antigens has been increasing exponentially, but this exponential increase is likely to tail off eventually as the highly expressed antigens are discovered and only the rarer, lower-expressing molecules remain to be discovered and assigned a CD number. Eventually the list of CD antigens should be complete and this will then encompass all human cell surface leukocyte differentiation antigens and their homologues in other mammalian and non-mammalian species.
It should be noted that although CD antigens were initially defined and characterised on the basis of the fact that they are expressed on the cell surface where they are associated with the cell membrane of human leukocytes, including lymphocytes (e.g., T cells, B cells), monocytes (e.g., macrophages) and granulocytes (e.g., neutrophils, eosinophils and basophils), CD antigens have also been found on the surface of other blood borne cells, such as stem cells, erythrocytes and megakaryocytes, Furthermore there are CD antigens that are expressed on the cell surface of cells and tissues which are not typically part of the immune system, and include cells from tissues such as the brain, liver, kidney, epithelial cells, etc. A subset of the cell surface CD antigens expressed in non-immune tissues are tissue specific CD antigens that are expressed predominantly in a specific tissue or tissues. Thus, CD molecules are ubiquitous and are expressed in differing amounts in every tissue in the body.
Historically, cell surface CD antigens have been used as diagnostic markers. Indeed, leukemias are diagnosed on the basis of cell morphology, the expression of particular cell surface CD antigens, enzyme activities and cytogenetic abnormalities such as chromosome translocations. The expression of at least three cell surface CD antigens on leukaemia cells can be determined using labelled antibodies to particular CD antigens using flow cytometric analysis.
Significantly, however, it has been observed that the CD antigens usually expressed at the cell surface may also be found as a soluble (sCD) form that is released into the blood (serum, plasma or whole blood) and into other body fluids including, for example, cerebrospinal fluid (CSF), urine, saliva, ascitic fluid, peritoneal fluid, uveal fluid, synovial fluid, pleural fluid. These CD molecules can be secreted from cells as a result of “active” processes such as alternative splicing (Woolfson and Milstein, PNAS, 91 (14) 6683-6687 (1994)) or by “passive” processes, such as cell surface shedding. Thus, CD molecules can be found in three different forms, (i) cell surface (membrane associated) CD molecules, (ii) secreted (shed or soluble) CD molecules, (sCD) produced by alternative splicing or other mechanisms and (iii) intracellular CD molecules (that remain within the cell cytoplasm). Each of these three classes of CD molecules can be complete molecules or fragments derived from them as a result of alternative splicing. These different isoforms may also have differential post-translational modifications, such as glycosylation.
Recent studies (see WO 00/39580) have described a system for the diagnosis of haematological malignancies, whereby immunoglobulins are immobilized on a solid support and used to detect cell-surface CD antigen levels, in particular cell-surface CD antigen levels in samples of whole cells. Using this approach, a pattern of expression of cell surface bound CD antigens is generated, which one of the inventors (Dr Adrian Woolfson) and others have shown to be indicative of the presence of various defined leukemias in a patient. However, this cell-surface based system of diagnosis is burdened with several disadvantages that are also applicable to the diagnosis of diseases and disorders that are not hematological. First, because the technique is cell-based, it has the associated disadvantages of having an undesirable amount of background noise and difficulty in measuring antigen levels accurately. Such methods furthermore only allow semi-quantitative determination of the relative densities of sub-populations of cells of distinct immunophenotypes, indeed absolute quantification using this method may not be possible, even in principle. Another problem with this cell-based method is that at equilibrium, the number of cells captured by the immobilised CD ligand dot, (antibody dot), depends not only on the affinities of the interactions, but also on the concentration of the CD ligand, (antibody), on the dot and the level of expression of the CD antigen on the cell surface. And in addition to this, there is the issue of the stereochemical availability and accessibility of the CD ligand, (monoclonal antibody), immobilized on the nitrocellulose membrane of the CD antibody array.
Furthermore, computerized quantification of the cell density as indicated by the pixel intensity corresponding to each dot of arrayed antibody depends not only on the number of cells in the test sample, but also on cell size and morphology. In addition to all these factors, the absolute requirement for purification of cells from whole blood, and the possible need to fractionate blood cells still further, makes such a cell-based approach both labor intensive and time consuming. Importantly though, a cell-based approach only provides a pattern of CD antigens expressed on the cell surface and does not take into account soluble CD antigens that are secreted from the cell or shed from the cell surface (sCD antigens). Therefore, there exists a need in the art for a simple method for diagnosis of a disease, disorder or condition, in which the limitations of the above described cell-surface based system are overcome, and for a complete, sensitive and specific profile of a disease which is obtained from an individual in a reliable and practical manner.